Solving A value is trying to be set on a copy of a slice from a DataFrame

Question

I am getting following warning:

SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

on following line:

df3[['prod_tags_0', 'prod_tags_1', 'prod_tags_2', 'prod_tags_3']].fillna(0, inplace=True)

How I can solve this warning ?

Answer 1

df3[['prod_tags_0', 'prod_tags_1', 'prod_tags_2', 'prod_tags_3']] creates a new dataframe which is a subset of df3. Since you are using inplace=True you are getting the aforementioned warning since it tries to modify the new dataframe inplace, to which you don't keep a reference around (and I suspect that if you'd print df3 you will see that this line actually had no effect).

I'd do one of the following:

1. re-assign the newly created dataframe back to df3 without using inplace=True:

   df3[['prod_tags_0', 'prod_tags_1', 'prod_tags_2', 'prod_tags_3']] = \
   df3[['prod_tags_0', 'prod_tags_1', 'prod_tags_2', 'prod_tags_3']].fillna(0)
   

Or the slightly preferable way (in my opinion at least):

2. Pass fillna the columns that you want to modify as a dictionary. The keys are the columns' names and the values are what NaN should be replaced with in each column:

   df3.fillna({'prod_tags_0': 0, 'prod_tags_1': 0,
               'prod_tags_2': 0, 'prod_tags_3': 0}, inplace=True)
   

   In this example you can use dictionary comprehension:

   import pandas as pd
   import numpy as np
   
   df = pd.DataFrame({'prod_tags_0': [np.nan], 'prod_tags_1': [np.nan], 
                      'prod_tags_2': [np.nan]})
   
   print(df)
   >>     prod_tags_0  prod_tags_1  prod_tags_2
       0          NaN          NaN          NaN   
   
   df.fillna({'prod_tags_' + str(i): 0 for i in range(2)}, inplace=True)
   
   print(df)
   
   >>     prod_tags_0  prod_tags_1  prod_tags_2
       0          0.0          0.0          NaN